Update app.py

app.py

@@ -1,7 +1,37 @@
 import gradio as gr
+import joblib
+
+# Function to load your model (adjust the path and method if needed)
+def load_model():
+    # This path is relative to the root of your Hugging Face Space
+    model_path = "./en-hate-speech-detection-3label"
+    model = joblib.load(model_path)
+    return model
+
+# Function to predict hate speech from text input
+def predict_hate_speech(text):
+    model = load_model()  # Load your model
+    prediction = model.predict([text])
+    # Assuming your model outputs integers representing classes, you might want to convert
+    # these to more readable labels. Adjust these labels according to your model's output.
+    labels = {0: 'Neutral or Ambiguous', 1: 'Not Hate', 2: 'Offensive or Hate Speech'}
+    return labels[prediction[0]]
+
+# Adjusted Gradio interface to take text input and output model predictions
+iface = gr.Interface(fn=predict_hate_speech, 
+                     inputs=gr.inputs.Textbox(lines=2, placeholder="Enter Text Here..."), 
+                     outputs="text", 
+                     description="Detects hate speech in text. Outputs 'No Hate Speech', 'Offensive Language', or 'Hate Speech'.")
+iface.launch()
+
+
+
+"""
+import gradio as gr
 
 def greet(name):
     return "Hello " + name + "!!"
 
 iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()
+"""